Intelligent prediction method, system, device and storage medium for pavement maintenance time

Abstract

The present application relates to the technical field of road maintenance, and discloses an intelligent prediction method, system, device and storage medium for pavement maintenance time. The method comprises obtaining a construction technical document of a target road section to determine a corresponding target technical identification and initial maintenance cycle information; obtaining vehicle monitoring information and road meteorological information of the target road section; obtaining pavement inspection data to calculate a pavement quality index, and generating several factor index-time relationship information based on the vehicle monitoring information, road meteorological information and pavement quality index of several road sections corresponding to the target technical identification to create a pavement degradation model; obtaining vehicle monitoring prediction information and road meteorological prediction information of the target road section and inputting them into the pavement degradation model to generate index time prediction data, and calculating and correcting maintenance time information based on the index time prediction data and several preset pavement maintenance thresholds; the present application has the effect of improving the reliability of road maintenance.

Description

Technical Field

[0001] The present application relates to the technical field of road maintenance, and in particular to an intelligent prediction method, system, device and storage medium for road maintenance time. Background Art

[0002] After a road is built and opened to traffic, it will gradually age and become damaged due to the passage of vehicles, erosion by meteorological factors, and traffic accidents. In order to ensure traffic safety and smooth traffic, the road needs to be maintained regularly. At present, the main way to maintain roads is to perform maintenance of varying degrees regularly according to specific cycles. However, there are differences in traffic loads, meteorological factors, etc. for different roads. Therefore, for the above-mentioned related technologies, the method of regularly maintaining roads according to specific cycles has the problem of difficulty in ensuring the reliability of road traffic conditions. Summary of the invention

[0003] In order to improve the reliability of road maintenance, the present application provides an intelligent prediction method, system, device and storage medium for road maintenance time.

[0004] The first invention objective of this application is achieved by adopting the following technical solution:

[0005] Intelligent prediction method for pavement maintenance time, including:

[0006] Obtain the construction technical documents of the target road section to determine the corresponding target technical identification and initial maintenance cycle information;

[0007] Obtain vehicle monitoring information from the target road section monitoring station and upstream and downstream monitoring stations, and obtain road weather information corresponding to the target road section;

[0008] Obtaining road inspection data to calculate a road quality index, generating several factor index time relationship information based on vehicle monitoring information, road weather information and road quality index corresponding to several road sections identified by the target technology, and creating a road deterioration model based on the several factor index time relationship information;

[0009] Obtaining vehicle monitoring prediction information and road weather prediction information of the target road section and inputting them into the road degradation model, generating exponential time prediction data, and calculating the corrected maintenance time information based on the exponential time prediction data and a number of preset road maintenance thresholds;

[0010] The initial maintenance cycle information includes several levels of standard cycles of the target road section; the vehicle monitoring information includes several passing vehicle identifications and vehicle load data; and the road meteorological information includes several meteorological factor data related to road surface deterioration.

[0011] By adopting the above technical scheme, the construction technical documents corresponding to the target road section are obtained in order to determine the performance standards of the target road section, and the corresponding target technical identification and initial maintenance cycle information are determined, so as to facilitate the subsequent search for road sections constructed with the same technical standards, as well as the default time for various levels of maintenance work; vehicle monitoring information is obtained from the target road section and monitoring stations at its upstream and downstream to obtain the number and load conditions of vehicles passing through the target road section, and the road meteorological information of the target road section is obtained to subsequently evaluate the wear and deterioration of the road surface of the target road section under the influence of vehicle driving and meteorological factors; road inspection data is obtained to obtain the actual wear and deterioration of the road surface, and the road quality index is calculated based on the road inspection data, and the vehicle monitoring information of several sections corresponding to the target technical identification is obtained. , road meteorological information and pavement quality index to generate information on the time relationship of several factor indices, so as to analyze the relationship between the pavement quality index and time of the target section of road under the influence of vehicle driving and meteorological factors, and to create a pavement degradation model based on the information on the time relationship of several factor indices, so as to facilitate the subsequent prediction of the pavement degradation of the target section of road; obtain the vehicle monitoring prediction information and road meteorological prediction information of the target section of road and input them into the pavement degradation model to analyze the change of the pavement quality index over time in the future, and then generate index time prediction data, compare the index time prediction data with several preset pavement maintenance thresholds, and then determine the time of a future road maintenance work, and generate corrected maintenance time information, so as to improve the reliability of the road maintenance time determination.

[0012] In a preferred example of the present application, the road inspection data is obtained to calculate the road quality index, and the calculation formula of the road quality index is:

[0013] PQI t =X 1t P1+X 2t P2+X 3t P3+X 4t P4

[0014] Among them, the PQI t is the road quality index at time t. The road inspection data at time t includes the flatness parameter X 1t , damage parameter X 2t , bearing capacity parameter X 3t , Anti-slip ability parameter X 4t , P1, P2, P3, and P4 are the weight coefficients corresponding to each road inspection data.

[0015] By adopting the above technical solution, road surface inspection data is obtained during daily road surface inspections, so that the road surface quality index can be calculated based on various inspection indicators and corresponding weight coefficients, so as to understand the current road surface quality and facilitate the subsequent creation of a road surface degradation model.

[0016] In a preferred example of the present application, the vehicle monitoring information, road weather information and road quality index corresponding to several road sections based on the target technical identification are used to generate several factor index time relationship information, and a road degradation model is created based on the several factor index time relationship information, including:

[0017] Based on the target technical identifier, vehicle monitoring information, road weather information and pavement quality index of the same road section are obtained and input into the data law analysis model, and the influence of each factor item in the vehicle monitoring information and road weather information on the pavement quality index accumulated over time is analyzed to generate a plurality of factor index time relationship information;

[0018] Create a pavement degradation model based on the initial pavement quality index and the time relationship information of several factor indices;

[0019] The technical identifier refers to an identifier used to distinguish technical indicators of road sections; the factor item refers to a factor item that may cause damage to the road surface quality; and the road surface degradation model refers to an algorithm model used to evaluate the reduction of the road surface quality index due to the influence of various factor items.

[0020] By adopting the above technical solution, the target technical identification is determined, and the vehicle monitoring information, road meteorological information and pavement quality index of several similar road sections are obtained. The data is processed through a data regularity analysis model to analyze the impact of each factor item on the pavement quality index accumulated over time, and then generate several factor index time relationship information to be used for evaluating the impact of a single factor item on the pavement quality index accumulated over time; based on the initial pavement quality index and the time relationship information of several factor indices, a pavement degradation model is created to subsequently evaluate the impact of multiple factor items on the pavement quality index accumulated over time.

[0021] In a preferred example of the present application: the vehicle monitoring information also includes vehicle lane information and vehicle speed information associated with the passing vehicle identification; and also includes:

[0022] Evaluate the lane average speed and lane change rate of each lane based on the vehicle monitoring information of the target road section;

[0023] Based on the target technical identifier, the lane average speed, lane change rate, road weather information and pavement quality index of each lane of the same road section are obtained and input into the data law analysis model, and the influence of different pavement quality indexes on the lane average speed and lane change rate of each lane under several weather conditions is analyzed to generate several average speed index relationship information and lane change rate index relationship information;

[0024] Determine an average speed threshold and a lane change rate threshold for each lane according to a number of average speed index relationship information, lane change rate index relationship information and a preset minimum road quality index;

[0025] The lane average speed and lane change rate of each lane are compared with the corresponding average speed threshold and lane change rate threshold, and when the average speed of any lane is lower than the corresponding average speed threshold or the lane change rate of any lane is higher than the corresponding lane change rate threshold, a lane maintenance alarm message is generated;

[0026] The lane change rate refers to the quotient of the number of changes in the passing vehicle identification of vehicles exiting the lane that is different from the passing vehicle identification of vehicles entering the lane and the number of vehicles entering the lane. When the number of vehicles exiting the lane is less than the number of vehicles entering the lane, a preset distinguishing identification of the number of shortfalls is added to the passing vehicle identification information of the vehicles exiting the lane, and the preset distinguishing identification should be different from any possible passing vehicle identification.

[0027] By adopting the above technical solution, the vehicle monitoring information also includes the vehicle lane information and vehicle speed information corresponding to each passing vehicle identification so as to further evaluate the lane average speed and lane change rate of each lane, so as to facilitate the subsequent evaluation of the traffic conditions of each lane; based on the target technical identification, the lane average speed, lane change rate, road weather information and pavement quality index of the same lane are obtained, and the data regularity analysis model is used to analyze the influence of different pavement quality indexes on the lane average speed and lane change rate of each lane under several meteorological conditions, so as to determine several average speed index relationship information and lane change rate index relationship information; according to several average speed index relationship information, lane change rate index relationship information and the preset minimum pavement quality index, the average speed threshold and lane change rate threshold of each lane are determined; the lane average speed and lane change rate of each lane are compared with the corresponding average speed threshold and lane change rate threshold. When the average speed of any lane is lower than the corresponding average speed threshold or the lane change rate of any lane is higher than the corresponding lane change rate threshold, it means that the lane may have road damage, traffic accidents or obstacles that are not conducive to vehicle driving, so it is necessary to generate lane maintenance alarm information to prompt road maintenance personnel to deal with it in time.

[0028] In a preferred example of the present application: the lane maintenance alarm information includes a road section mark and a lane mark;

[0029] When the average speed of any lane is lower than the corresponding average speed threshold or the lane change rate of any lane is higher than the corresponding lane change rate threshold, after the lane maintenance alarm information is generated, the method further includes:

[0030] Determine the target road section to be maintained and the target lane to be maintained based on the lane maintenance alarm information, determine the traffic flow data of the target road section to be maintained based on the vehicle monitoring information, determine the number of lanes on both sides of the target lane to be maintained, define the lane on the side with fewer lanes as a narrow side lane, and define the lane on the side with more lanes as a wide side lane;

[0031] The traffic flow data and the preset congestion classification rules are used to determine the congestion level of the target road section to be maintained, wherein the congestion level includes low level, medium level and high level;

[0032] When the congestion level of the target road section to be maintained is high, the target lane to be maintained is determined as the maintenance lane; when the congestion level of the target road section to be maintained is medium, the target lane to be maintained and the narrow side lane are defined as the maintenance lane; when the congestion level of the target road section to be maintained is low, the target lane to be maintained and the wide side lane are defined as the maintenance lane;

[0033] Based on the ratio of the maintenance lanes to the total number of lanes in the target road section to be maintained, the corresponding quality index recovery value is calculated to reset the initial pavement quality index of the pavement degradation model;

[0034] The maintenance lane refers to a lane that needs to perform maintenance work; when the number of lanes on both sides of the target lane to be maintained is equal, the slow lane is defined as a narrow side lane; when the number of narrow side lanes is 0, a lane in the wide side lane away from the target lane to be maintained is defined as an exclusion maintenance lane, and the exclusion maintenance lane cannot be defined as a maintenance lane.

[0035] By adopting the above technical solution, the lane maintenance alarm information includes a road section mark and a lane mark, which are used to determine the target road section to be maintained and the target lane to be maintained; the traffic flow data of the target road section to be maintained is determined based on the vehicle monitoring information, so as to subsequently analyze the congestion degree of the target road section to be maintained; the narrow side lane and the wide side lane are defined based on the number of lanes on both sides of the target lane to be maintained, so as to subsequently implement different road maintenance work plans according to the road congestion degree; the congestion level of the target road section to be maintained is determined based on the traffic flow data and the preset congestion classification rules, so as to evaluate the congestion degree of the target road section to be maintained; when the target road section to be maintained is highly congested, only the target lane to be maintained is confirmed. The target road section to be maintained is designated as the maintenance lane to minimize the impact of vehicle congestion caused by road maintenance work. When the target road section to be maintained is of medium congestion, the target road section to be maintained and the narrow side lane are defined as the maintenance lane, so as to increase the maintenance scope of this road maintenance work when the traffic volume is medium, so as to improve the maintenance efficiency. When the target road section to be maintained is of low congestion, the target lane to be maintained and the wide side lane are defined as the maintenance lane, so as to further increase the maintenance scope of this road maintenance work, thereby further improving the maintenance efficiency. The quality index recovery value is calculated according to the proportion of the maintenance lanes, so as to reset the initial pavement quality index in the pavement degradation model according to the actual maintenance effect.

[0036] The second invention objective of this application is achieved by the following technical solution:

[0037] An intelligent prediction system for pavement maintenance time, applied to any of the intelligent prediction methods for pavement maintenance time described above, comprises:

[0038] A target technical identification acquisition module is used to acquire the construction technical documents of the target road section to determine the corresponding target technical identification and initial maintenance cycle information;

[0039] The vehicle weather information acquisition module is used to obtain the vehicle monitoring information of the target road section monitoring station and the upstream and downstream monitoring stations, and obtain the road weather information corresponding to the target road section;

[0040] A pavement degradation model creation module is used to obtain pavement inspection data to calculate a pavement quality index, generate time relationship information of several factor indices based on vehicle monitoring information, road weather information and pavement quality index corresponding to several road sections of the target technical identification, and create a pavement degradation model based on the time relationship information of several factor indices;

[0041] A modified maintenance time calculation module is used to obtain vehicle monitoring prediction information and road weather prediction information of the target road section and input them into the road degradation model to generate index time prediction data, and calculate the modified maintenance time information based on the index time prediction data and a plurality of preset road maintenance thresholds;

[0042] The initial maintenance cycle information includes several levels of standard cycles of the target road section; the vehicle monitoring information includes several passing vehicle identifications and vehicle load data; and the road meteorological information includes several meteorological factor data related to road surface deterioration.

[0043] In a preferred example, the present application also includes:

[0044] A lane state evaluation module is used to evaluate the lane average speed and lane change rate of each lane based on the vehicle monitoring information of the target road section;

[0045] The lane state index relationship analysis module is used to obtain the lane average speed, lane change rate, road weather information and pavement quality index of each lane of the same road section based on the target technical identification and input them into the data law analysis model to analyze the influence of different pavement quality indexes on the lane average speed and lane change rate of each lane under several weather conditions, so as to generate several average speed index relationship information and lane change rate index relationship information;

[0046] A lane-related threshold determination module, used to determine an average speed threshold and a lane change rate threshold of each lane according to a number of average speed index relationship information, lane change rate index relationship information and a preset minimum road quality index;

[0047] A lane maintenance alarm information generating module is used to compare the lane average speed and lane change rate of each lane with the corresponding average speed threshold and lane change rate threshold, and generate lane maintenance alarm information when the average speed of any lane is lower than the corresponding average speed threshold or the lane change rate of any lane is higher than the corresponding lane change rate threshold;

[0048] The vehicle monitoring information also includes vehicle lane information and vehicle speed information associated with the passing vehicle identification; the lane change rate refers to the quotient of the number of changes in the passing vehicle identification of vehicles leaving the lane that is different from the passing vehicle identification of vehicles entering the lane and the number of vehicles entering the lane. When the number of vehicles leaving the lane is less than the number of vehicles entering the lane, a preset distinguishing mark of the number of shortages is added to the passing vehicle identification information of the vehicles leaving the lane, and the preset distinguishing mark should be different from any possible passing vehicle identification.

[0049] In a preferred example, the present application also includes:

[0050] A target lane to be maintained analysis module is used to determine a target road section to be maintained and a target lane to be maintained based on lane maintenance alarm information, determine traffic flow data of the target road section to be maintained based on the vehicle monitoring information, determine the number of lanes on both sides of the target lane to be maintained, define the lane on the side with fewer lanes as a narrow side lane, and define the lane on the side with more lanes as a wide side lane;

[0051] A congestion level determination module is used to determine the congestion level of the target road section to be maintained by combining the traffic flow data and the preset congestion classification rules, wherein the congestion levels include low level, medium level and high level;

[0052] A maintenance lane determination module is used to determine the target lane to be maintained as the maintenance lane when the congestion level of the target road section to be maintained is high, define the target lane to be maintained and the narrow side lane as the maintenance lane when the congestion level of the target road section to be maintained is medium, and define the target lane to be maintained and the wide side lane as the maintenance lane when the congestion level of the target road section to be maintained is low;

[0053] A pavement quality initial index resetting module is used to calculate a corresponding quality index recovery value based on the ratio of the maintenance lanes to the total number of lanes in the target road section to be maintained, so as to reset the pavement quality initial index of the pavement degradation model;

[0054] The lane maintenance alarm information includes a road section mark and a lane mark; the maintenance lane refers to a lane that needs to perform maintenance work; when the number of lanes on both sides of the target lane to be maintained is equal, the slow lane is defined as a narrow side lane; when the number of narrow side lanes is 0, a lane in the wide side lane that is far away from the target lane to be maintained is defined as an exclusion maintenance lane, and the exclusion maintenance lane cannot be defined as a maintenance lane.

[0055] The third invention objective of this application is achieved by the following technical solution:

[0056] A computer device comprises a memory, a processor and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the intelligent prediction method for pavement maintenance time are implemented.

[0057] The fourth invention objective of this application is achieved by the following technical solution:

[0058] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of the above-mentioned intelligent prediction method for pavement maintenance time.

[0059] In summary, the present application includes at least one of the following beneficial technical effects:

[0060] 1. Obtain the construction technical documents corresponding to the target road section in order to determine the performance standards of the target road section, and determine the corresponding target technical identification and initial maintenance cycle information, so as to facilitate the subsequent search for road sections constructed with the same technical standards, as well as the default time for various levels of maintenance work; obtain vehicle monitoring information from the target road section and its upstream and downstream monitoring stations in order to know the number and load conditions of vehicles passing through the target road section, and obtain road meteorological information of the target road section in order to subsequently evaluate the wear and deterioration of the road surface of the target road section under the influence of vehicle driving and meteorological factors; obtain road surface inspection data in order to know the actual wear and deterioration of the road surface, calculate the road surface quality index based on the road surface inspection data, and calculate the road surface quality index based on the vehicle monitoring information and road meteorological information of several sections corresponding to the target technical identification. The information and the road quality index are used to generate the time relationship information of several factor indices, so as to analyze the relationship between the road quality index and time of the road surface of the target section under the influence of vehicle driving and meteorological factors. A road degradation model is created according to the time relationship information of several factor indices, so as to facilitate the subsequent prediction of the road degradation of the target section. The vehicle monitoring prediction information and the road meteorological prediction information of the target section are obtained and input into the road degradation model, so as to analyze the change of the road quality index over time in the future, and then generate the index time prediction data, compare the index time prediction data with several preset road maintenance thresholds, and then determine the time of a future road maintenance work, and generate the revised maintenance time information, so as to improve the reliability of the road maintenance time determination.

[0061] 2. The vehicle monitoring information also includes the vehicle lane information and vehicle speed information corresponding to each passing vehicle identification so as to further evaluate the lane average speed and lane change rate of each lane, so as to facilitate the subsequent evaluation of the traffic conditions of each lane; based on the target technical identification, the lane average speed, lane change rate, road weather information and pavement quality index of the same lane are obtained, and the data regularity analysis model is used to analyze the influence of different pavement quality indexes on the lane average speed and lane change rate of each lane under several meteorological conditions, and then determine several average speed index relationship information and lane change rate index relationship information; according to several average speed index relationship information, lane change rate index relationship information and the preset minimum pavement quality index, the average speed threshold and lane change rate threshold of each lane are determined; the lane average speed and lane change rate of each lane are compared with the corresponding average speed threshold and lane change rate threshold. When the average speed of any lane is lower than the corresponding average speed threshold or the lane change rate of any lane is higher than the corresponding lane change rate threshold, it means that the lane may have road damage, traffic accidents or obstacles that are not conducive to vehicle driving, so it is necessary to generate lane maintenance alarm information to prompt road maintenance personnel to deal with it in time.

[0062] 3. Lane maintenance alarm information includes road section identification and lane identification, which are used to determine the target road section to be maintained and the target lane to be maintained. The traffic flow data of the target road section to be maintained is determined based on the vehicle monitoring information, so as to analyze the congestion level of the target road section to be maintained later. The narrow side lane and the wide side lane are defined based on the number of lanes on both sides of the target lane to be maintained, so as to implement different road maintenance work plans according to the road congestion level. The congestion level of the target road section to be maintained is determined based on the traffic flow data and the preset congestion classification rules, so as to evaluate the congestion level of the target road section to be maintained. When the target road section to be maintained is highly congested, only the target lane to be maintained is determined as the lane to be maintained. The maintenance lane is defined as a maintenance lane to minimize the impact of vehicle congestion caused by road maintenance work. When the target section to be maintained is medium-level congested, the target section to be maintained and the narrow side lane are defined as maintenance lanes, so as to increase the maintenance scope of this road maintenance work when the traffic volume is medium, so as to improve the maintenance efficiency. When the target section to be maintained is low-level congested, the target lane to be maintained and the wide side lane are defined as maintenance lanes, so as to further increase the maintenance scope of this road maintenance work, thereby further improving the maintenance efficiency. The quality index recovery value is calculated according to the proportion of maintenance lanes, so as to reset the initial pavement quality index in the pavement degradation model according to the actual maintenance effect. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] Figure 1 It is a flow chart of the intelligent prediction method for pavement maintenance time in Example 1 of the present application.

[0064] Figure 2 It is a principle block diagram of the intelligent prediction system for pavement maintenance time in Example 2 of the present application.

[0065] Figure 3 It is a schematic diagram of the equipment in Example 3 of the present application. DETAILED DESCRIPTION

[0066] The following is combined with Figures 1 to 3 This application is described in further detail.

[0067] Embodiment 1

[0068] Reference Figure 1 The present application discloses an intelligent prediction method for pavement maintenance time, which specifically comprises the following steps:

[0069] S10: Acquire the construction technology document of the target road section to determine the corresponding target technology identification and initial maintenance cycle information.

[0070] In this embodiment, the construction technical documents include construction drawings, technical indicators and other technical documents that can be used to determine road quality performance indicators; the target technical identifier refers to an identifier used to distinguish the quality performance indicators of road sections, and sections with the same quality performance indicators are marked with the same target technical identifier; the initial maintenance cycle information includes several levels of standard cycles for maintaining the target road sections.

[0071] Specifically, the construction technology documents corresponding to the target road section are obtained in order to determine the performance standards of the target road section, and the corresponding target technology identification and initial maintenance cycle information are determined to facilitate subsequent searches for road sections constructed with the same technical standards, as well as the default time for various levels of maintenance work.

[0072] S20: Obtain vehicle monitoring information from the target road section monitoring station and upstream and downstream monitoring stations, and obtain road weather information corresponding to the target road section.

[0073] In this embodiment, the target section monitoring station refers to a monitoring station set up in the target section for monitoring vehicle monitoring information, and the upstream and downstream monitoring stations refer to monitoring stations set up in the previous section and the next section of the target section. The monitoring stations may specifically include cameras, speed radars, ETC identifiers and other monitoring equipment; vehicle monitoring information includes a number of passing vehicle identifications and vehicle load data; road meteorological information includes a number of meteorological factor data related to road surface degradation, such as rainfall, temperature, light intensity, etc.

[0074] Specifically, vehicle monitoring information is obtained from the target section and monitoring stations upstream and downstream thereof to learn the number and load conditions of vehicles passing through the target section, and road meteorological information of the target section is obtained to subsequently evaluate the wear and degradation of the road surface of the target section under the influence of vehicle driving and meteorological factors.

[0075] S30: Obtain road inspection data to calculate a road quality index, generate several factor index time relationship information based on the vehicle monitoring information, road weather information and road quality index of several road sections corresponding to the target technical identification, and create a road degradation model based on the several factor index time relationship information.

[0076] In this embodiment, the road surface inspection data refers to the data used to calculate the road surface quality index, and the specific items can be set and adjusted according to actual needs.

[0077] Specifically, pavement inspection data is acquired based on a preset inspection cycle in order to learn the actual wear and tear deterioration of the pavement, wherein the inspection cycle can be determined according to actual needs, and the inspection cycle is preferably one day; a pavement quality index is calculated based on the pavement inspection data, and vehicle monitoring information, road meteorological information and pavement quality index of several sections corresponding to the target technical identifier are used to generate several factor index time relationship information, so as to facilitate the analysis of the relationship between the pavement quality index of the target section and time when the pavement is affected by vehicle driving and meteorological factors, and to create a pavement degradation model based on the several factor index time relationship information, so as to facilitate the subsequent prediction of the pavement degradation of the target section.

[0078] The calculation formula of the road quality index is:

[0079] PQI t =X 1t P1+X 2t P2+X 3t P3+X 4t P4

[0080] Among them, the PQI t is the road quality index at time t. The road inspection data at time t includes the flatness parameter X 1t , damage parameter X 2t , bearing capacity parameter X 3t , Anti-slip ability parameter X 4t , P1, P2, P3, and P4 are the weight coefficients corresponding to each road inspection data.

[0081] In this embodiment, the specific calculation formula of the pavement quality index and the selected indicators can be obtained from the prior art and supplemented into the above calculation formula, and will not be elaborated in this specification.

[0082] Specifically, during the daily road inspection, road inspection data is obtained so that the road quality index can be calculated based on various inspection indicators and corresponding weight coefficients, so as to know the current road quality and facilitate the subsequent creation of a road degradation model.

[0083] Wherein, in step S30, it includes:

[0084] S31: Based on the target technical identifier, the vehicle monitoring information, road weather information and pavement quality index of the same road section are obtained and input into the data regularity analysis model, and the influence of each factor item in the vehicle monitoring information and road weather information on the pavement quality index accumulated over time is analyzed to generate a plurality of factor index time relationship information.

[0085] In this embodiment, the technical identifier refers to an identifier used to distinguish the technical indicators of a road section; the factor item refers to a factor item that may cause damage to the road quality; each data of the vehicle monitoring information, road meteorological information and road quality index includes a corresponding detection time node and a calculation time node; the factor item refers to a factor item that may affect the road quality index; the factor index time relationship information refers to the relationship information used to record the impact of the accumulation of data of a single factor item on the road quality index over time, for example, when the factor item is rainfall, the corresponding factor index time relationship information may include the relationship information of the road quality index changing with time under the environment of rainfall in a specific numerical range; since the relationship of the road quality index changing with time under the combined effect of multiple factor items can be analyzed from the relationship of the road quality index changing with time under the action of a single factor item, it can be essentially converted into a problem of solving a multivariate function, therefore, the data regularity analysis model has a built-in artificial intelligence algorithm for analyzing the relationship between multiple data, which can be specifically a neural network algorithm, for analyzing the relationship information of the road quality index changing with time under the combined effect of a large number of inputs, so as to evaluate the relationship information of the road quality index changing with time under the action of a single factor item.

[0086] Specifically, the target technical identification is determined, and vehicle monitoring information, road meteorological information and pavement quality index of several similar road sections are obtained. The data are processed through a data regularity analysis model to analyze the impact of each factor item on the pavement quality index accumulated over time, and then several factor index time relationship information is generated to evaluate the impact of a single factor item on the pavement quality index accumulated over time.

[0087] S32: Creating a pavement degradation model based on the initial pavement quality index and time relationship information of several factor indices.

[0088] In this embodiment, the pavement degradation model refers to an algorithm model used to evaluate the pavement quality index that is reduced due to the influence of various factors; the initial pavement quality index refers to the pavement quality index measured by the pavement quality index calculation method just after the road maintenance work is completed.

[0089] Specifically, based on the initial pavement quality index and the time relationship information of several factor indices, a pavement degradation model is created to subsequently evaluate the impact of multiple factor items on the pavement quality index accumulated over time.

[0090] S40: Obtain vehicle monitoring prediction information and road weather prediction information of the target road section and input them into the road degradation model to generate exponential time prediction data, and calculate the corrected maintenance time information based on the exponential time prediction data and a plurality of preset road maintenance thresholds.

[0091] In this embodiment, vehicle monitoring prediction information refers to information obtained by predicting vehicle monitoring information; road weather prediction information refers to information obtained by predicting road weather information; index time prediction data refers to the predicted value of the road quality index calculated based on the vehicle monitoring prediction information and the road weather prediction information; the road maintenance threshold refers to the threshold set based on the minimum allowable value of the road quality index for the road to meet the normal use needs of vehicles; the road degradation model refers to an algorithm model used to calculate the index time prediction data based on the input vehicle monitoring prediction information and road weather prediction information.

[0092] Specifically, the vehicle monitoring prediction information and road weather prediction information of the target road section are obtained and input into the pavement degradation model in order to analyze the change of the future pavement quality index over time, and then generate index time prediction data, compare the index time prediction data with several preset pavement maintenance thresholds, calculate the time node when the index time prediction data reaches less than or equal to the pavement maintenance threshold as the corrected maintenance time information, and then determine the time of a future road maintenance work, and generate the corrected maintenance time information, so as to improve the reliability of the road maintenance time determination.

[0093] Among them, the intelligent prediction method of pavement maintenance time also includes:

[0094] S50: Evaluate the lane average speed and lane change rate of each lane based on the vehicle monitoring information of the target road section.

[0095] In this embodiment, the vehicle monitoring information also includes vehicle lane information and vehicle speed information associated with the passing vehicle identification; the lane change rate refers to the quotient of the number of changes in the passing vehicle identification of vehicles exiting the lane that is different from the passing vehicle identification of vehicles entering the lane and the number of vehicles entering the lane in a unit time or a specific statistical period. When the number of vehicles exiting the lane is less than the number of vehicles entering the lane, a preset distinguishing mark of the number of shortages is added to the passing vehicle identification information of the vehicles exiting the lane, wherein the preset distinguishing mark should be different from any possible passing vehicle identification; the lane average speed refers to the average speed of vehicles traveling in the lane in a unit time or a specific statistical period.

[0096] For example, during a statistical period of a certain road section, 10 vehicles enter lane A, with identification marks XXXXA, XXXXB, XXXXC, XXXXD, XXXXE, XXXXF, XXXXG, XXXXH, XXXXI, XXXXJ respectively; 8 vehicles leave lane A, with identification marks XXXXA, XXXXB, XXXXC, XXXXD, XXXXE, XXXXF, XXXXK, XXXXL, XXXX0, XXXX0 respectively, where XXXX0 is a preset distinguishing mark; then the lane change rate of the road section during the statistical period is 40%.

[0097] Specifically, when the road surface quality of a lane is poor, the driver will be prompted to reduce the speed when driving the vehicle in that lane, or change lanes. Therefore, the vehicle monitoring information also includes the vehicle lane information and vehicle speed information corresponding to each passing vehicle identification in order to further evaluate the lane average speed and lane change rate of each lane, so as to facilitate the subsequent evaluation of the traffic conditions of each lane.

[0098] S60: Based on the target technical identifier, the average lane speed, lane change rate, road weather information and pavement quality index of each lane of the same road section are obtained and input into the data law analysis model, and the influence of different pavement quality indices on the average lane speed and lane change rate of each lane under several weather conditions is analyzed to generate several average speed index relationship information and lane change rate index relationship information.

[0099] In this embodiment, the average speed index relationship information refers to the information used to record the relationship between the lane average speed and the road surface quality index when the meteorological conditions are determined; the lane change rate index relationship information refers to the information used to record the relationship between the lane change rate and the road surface quality index when the meteorological conditions are determined.

[0100] Specifically, the average lane speed, lane change rate, road weather information and pavement quality index of the same type of lanes are obtained based on the target technical identification, and the data are processed through a data regularity analysis model to analyze the influence of different pavement quality indices on the average lane speed and lane change rate of each lane under several meteorological conditions, and then determine several average speed index relationship information and lane change rate index relationship information.

[0101] Furthermore, the average speed index relationship information and the lane change rate index relationship information can also be differentiated according to the degree of road congestion, so as to analyze the relationship between the lane average speed, lane change rate and road surface quality index under different road congestion levels and certain meteorological conditions through different average speed index relationship information and lane change rate index relationship information.

[0102] S70: Determine an average speed threshold and a lane change rate threshold for each lane according to a plurality of average speed index relationship information, lane change rate index relationship information and a preset minimum road surface quality index.

[0103] In this embodiment, the minimum pavement quality index refers to the minimum permissible pavement quality index for a road to meet normal vehicle use requirements.

[0104] Specifically, the average speed threshold and lane change rate threshold of each lane are determined according to a number of average speed index relationship information, lane change rate index relationship information and a preset minimum road surface quality index.

[0105] S80: Compare the lane average speed and lane change rate of each lane with the corresponding average speed threshold and lane change rate threshold. When the average speed of any lane is lower than the corresponding average speed threshold or the lane change rate of any lane is higher than the corresponding lane change rate threshold, generate a lane maintenance alarm message.

[0106] Specifically, the lane average speed and lane change rate of each lane are compared with the corresponding average speed threshold and lane change rate threshold. When the average speed of any lane is lower than the corresponding average speed threshold or the lane change rate of any lane is higher than the corresponding lane change rate threshold, it means that the lane may have road damage, traffic accidents or obstacles that are not conducive to vehicle driving. Therefore, it is necessary to generate lane maintenance alarm information to prompt road maintenance personnel to deal with it in time.

[0107] Wherein, after step S80, the intelligent prediction method for pavement maintenance time further includes:

[0108] S90: Determine the target road section to be maintained and the target lane to be maintained based on the lane maintenance alarm information, determine the traffic flow data of the target road section to be maintained based on the vehicle monitoring information, determine the number of lanes on both sides of the target lane to be maintained, define the lane on the side with fewer lanes as a narrow side lane, and define the lane on the side with more lanes as a wide side lane.

[0109] In this embodiment, the lane maintenance alarm information includes a road section identifier and a lane identifier; the target lane to be maintained refers to a lane that requires road maintenance, and the target road section to be maintained refers to the road section where the target lane to be maintained is located.

[0110] Specifically, the lane maintenance alarm information includes road section identification and lane identification, which are used to determine the target road section to be maintained and the target lane to be maintained. The traffic flow data of the target road section to be maintained is determined based on the vehicle monitoring information, so as to subsequently analyze the congestion level of the target road section to be maintained. The narrow side lane and the wide side lane are defined based on the number of lanes on both sides of the target lane to be maintained, so as to subsequently implement different road maintenance work plans according to the road congestion level.

[0111] S100: Determine the congestion level of the target road section to be maintained by combining the traffic flow data and a preset congestion classification rule, wherein the congestion level includes a low level, a medium level and a high level.

[0112] In this embodiment, the congestion classification rule includes a rule for classifying the congestion level of a road section, specifically including three non-overlapping vehicle flow data value intervals.

[0113] Specifically, the congestion level of the target road section to be maintained is determined according to the traffic flow data and a preset congestion classification rule, so as to evaluate the congestion degree of the target road section to be maintained.

[0114] S110: When the congestion level of the target road section to be maintained is high, the target lane to be maintained is determined as the maintenance lane; when the congestion level of the target road section to be maintained is medium, the target lane to be maintained and the narrow side lane are defined as the maintenance lane; when the congestion level of the target road section to be maintained is low, the target lane to be maintained and the wide side lane are defined as the maintenance lane.

[0115] In this embodiment, the maintenance lane refers to the lane that needs to perform maintenance work; when the number of lanes on both sides of the target lane to be maintained is equal, the slow lane is defined as the narrow side lane; when the number of narrow side lanes is 0, a lane in the wide side lane far away from the target lane to be maintained is defined as an exclusion maintenance lane, and the exclusion maintenance lane cannot be defined as a maintenance lane.

[0116] Specifically, when the target road section to be maintained is at a high level of congestion, only the target lane to be maintained is determined as the maintenance lane to minimize the impact of vehicle congestion caused by road maintenance work. When the target road section to be maintained is at a medium level of congestion, the target road section to be maintained and the narrow side lane are defined as maintenance lanes to increase the maintenance scope of this road maintenance work when the traffic volume is medium to improve the maintenance efficiency. When the target road section to be maintained is at a low level of congestion, the target lane to be maintained and the wide side lane are defined as maintenance lanes to further increase the maintenance scope of this road maintenance work, thereby further improving the maintenance efficiency.

[0117] S120: Calculate a corresponding quality index recovery value based on the ratio of the maintenance lanes to be maintained relative to the total number of lanes in the target road section to be maintained, so as to reset the initial road quality index of the road deterioration model.

[0118] In this embodiment, when dividing the road section, the number of lanes in the same road section must be the same.

[0119] Specifically, the quality index recovery value is calculated according to the proportion of lanes undergoing maintenance, so as to reset the initial pavement quality index in the pavement degradation model according to the actual maintenance effect.

[0120] It should be understood that the serial numbers of the steps in the above embodiments do not imply a sequence of execution. The execution sequence of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0121] Embodiment 2

[0122] An intelligent prediction system for pavement maintenance time, which corresponds to the intelligent prediction method for pavement maintenance time in the above-mentioned embodiment.

[0123] like Figure 2 As shown in the figure, the intelligent prediction system for pavement maintenance time includes a target technical identification acquisition module, a vehicle weather information acquisition module, a pavement degradation model creation module and a modified maintenance time calculation module. The detailed description of each functional module is as follows:

[0124] A target technical identification acquisition module is used to acquire the construction technical documents of the target road section to determine the corresponding target technical identification and initial maintenance cycle information;

[0125] The vehicle weather information acquisition module is used to obtain the vehicle monitoring information of the target road section monitoring station and the upstream and downstream monitoring stations, and obtain the road weather information corresponding to the target road section;

[0126] A pavement degradation model creation module is used to obtain pavement inspection data to calculate a pavement quality index, generate time relationship information of several factor indices based on vehicle monitoring information, road weather information and pavement quality index corresponding to several road sections of the target technical identification, and create a pavement degradation model based on the time relationship information of several factor indices;

[0127] The modified maintenance time calculation module is used to obtain vehicle monitoring prediction information and road weather prediction information of the target road section and input them into the road degradation model to generate index time prediction data, and calculate the modified maintenance time information based on the index time prediction data and a plurality of preset road maintenance thresholds.

[0128] Among them, the pavement degradation model creation module also includes:

[0129] A factor index time relationship analysis submodule is used to obtain vehicle monitoring information, road weather information and pavement quality index of the same road section based on the target technical identifier and input them into the data law analysis model, analyze the influence of each factor item in the vehicle monitoring information and road weather information on the pavement quality index accumulated over time, so as to generate a number of factor index time relationship information;

[0130] The pavement degradation model generation submodule is used to create a pavement degradation model based on the initial pavement quality index and the time relationship information of several factor indices.

[0131] Among them, the intelligent prediction system of pavement maintenance time also includes:

[0132] A lane state evaluation module is used to evaluate the lane average speed and lane change rate of each lane based on the vehicle monitoring information of the target road section;

[0133] The lane state index relationship analysis module is used to obtain the lane average speed, lane change rate, road weather information and pavement quality index of each lane of the same road section based on the target technical identification and input them into the data law analysis model to analyze the influence of different pavement quality indexes on the lane average speed and lane change rate of each lane under several weather conditions, so as to generate several average speed index relationship information and lane change rate index relationship information;

[0134] A lane-related threshold determination module, used to determine an average speed threshold and a lane change rate threshold of each lane according to a number of average speed index relationship information, lane change rate index relationship information and a preset minimum road quality index;

[0135] The lane maintenance alarm information generation module is used to compare the lane average speed and lane change rate of each lane with the corresponding average speed threshold and lane change rate threshold. When the average speed of any lane is lower than the corresponding average speed threshold or the lane change rate of any lane is higher than the corresponding lane change rate threshold, a lane maintenance alarm information is generated.

[0136] A target lane to be maintained analysis module is used to determine a target road section to be maintained and a target lane to be maintained based on lane maintenance alarm information, determine traffic flow data of the target road section to be maintained based on the vehicle monitoring information, determine the number of lanes on both sides of the target lane to be maintained, define the lane on the side with fewer lanes as a narrow side lane, and define the lane on the side with more lanes as a wide side lane;

[0137] A congestion level determination module is used to determine the congestion level of the target road section to be maintained by combining the traffic flow data and the preset congestion classification rules, wherein the congestion levels include low level, medium level and high level;

[0138] A maintenance lane determination module is used to determine the target lane to be maintained as the maintenance lane when the congestion level of the target road section to be maintained is high, define the target lane to be maintained and the narrow side lane as the maintenance lane when the congestion level of the target road section to be maintained is medium, and define the target lane to be maintained and the wide side lane as the maintenance lane when the congestion level of the target road section to be maintained is low;

[0139] The pavement quality initial index resetting module is used to calculate the corresponding quality index recovery value based on the maintenance lane ratio of the maintenance lane to the total number of lanes in the target section to be maintained, so as to reset the pavement quality initial index of the pavement degradation model.

[0140] For the specific limitations of the intelligent prediction system for pavement maintenance time, please refer to the limitations of the intelligent prediction method for pavement maintenance time in the above text, which will not be repeated here; the various modules in the above-mentioned intelligent prediction system for pavement maintenance time can be implemented in whole or in part through software, hardware and their combination; the above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the corresponding operations of the above modules.

[0141] Embodiment 3

[0142] A computer device, which may be a server, may have an internal structure as shown in Figure 3 As shown. The computer device includes a processor, a memory, a network interface and a database connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store data such as construction technology documents, target technology identification, initial maintenance cycle information, vehicle monitoring information, road meteorological information, road surface inspection data, road surface quality index, factor index time relationship information, road surface degradation model, vehicle monitoring prediction information, road meteorological prediction information, index time prediction data, road surface maintenance threshold and corrected maintenance time information. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, an intelligent prediction method for road surface maintenance time is implemented.

[0143] In one embodiment, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the following steps when executing the computer program:

[0144] S10: Acquire the construction technology document of the target road section to determine the corresponding target technology identification and initial maintenance cycle information;

[0145] S20: Obtain vehicle monitoring information of the target road section monitoring station and upstream and downstream monitoring stations, and obtain road weather information corresponding to the target road section;

[0146] S30: Obtaining road inspection data to calculate a road quality index, generating time relationship information of several factor indices based on vehicle monitoring information, road weather information and road quality index corresponding to several road sections of the target technical identifier, and creating a road degradation model based on the time relationship information of the several factor indices;

[0147] S40: Obtain vehicle monitoring prediction information and road weather prediction information of the target road section and input them into the road degradation model to generate exponential time prediction data, and calculate the corrected maintenance time information based on the exponential time prediction data and a plurality of preset road maintenance thresholds.

[0148] In one embodiment, a computer readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented:

[0149] S10: Acquire the construction technology document of the target road section to determine the corresponding target technology identification and initial maintenance cycle information;

[0150] S20: Obtain vehicle monitoring information of the target road section monitoring station and upstream and downstream monitoring stations, and obtain road weather information corresponding to the target road section;

[0151] S30: Obtaining road inspection data to calculate a road quality index, generating time relationship information of several factor indices based on vehicle monitoring information, road weather information and road quality index corresponding to several road sections of the target technical identifier, and creating a road degradation model based on the time relationship information of the several factor indices;

[0152] S40: Obtain vehicle monitoring prediction information and road weather prediction information of the target road section and input them into the road degradation model to generate exponential time prediction data, and calculate the corrected maintenance time information based on the exponential time prediction data and a plurality of preset road maintenance thresholds.

[0153] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink), DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0154] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

[0155] The embodiments described above are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, it should be understood by those skilled in the art that the technical solutions described in the aforementioned embodiments may still be modified, or some of the features thereof may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. An intelligent prediction method for pavement maintenance time, characterized in that: include: Obtain the construction technical documents of the target road section to determine the corresponding target technical identification and initial maintenance cycle information; Obtain vehicle monitoring information from the target road section monitoring station and upstream and downstream monitoring stations, and obtain road weather information corresponding to the target road section; Obtaining road inspection data to calculate a road quality index, generating several factor index time relationship information based on vehicle monitoring information, road weather information and road quality index corresponding to several road sections identified by the target technology, and creating a road deterioration model based on the several factor index time relationship information; Obtaining vehicle monitoring prediction information and road weather prediction information of the target road section and inputting them into the road degradation model, generating exponential time prediction data, and calculating the corrected maintenance time information based on the exponential time prediction data and a number of preset road maintenance thresholds; The initial maintenance cycle information includes several levels of standard cycles of the target road section; the vehicle monitoring information includes several passing vehicle identifications and vehicle load data; the road weather information includes several meteorological factor data related to road surface deterioration; Wherein, in the acquisition of road inspection data to calculate the road quality index, the calculation formula of the road quality index is: PQI t =X 1t P1+X 2t P2+X 3t P3+X 4t P4 Among them, the PQI t is the road quality index at time t. The road inspection data at time t includes the flatness parameter X 1t , damage parameter X 2t , bearing capacity parameter X 3t , Anti-slip ability parameter X 4t , P1, P2, P3, and P4 are weight coefficients corresponding to each road inspection data; Construction technical documents include construction drawings and technical indicators, and refer to technical documents used to determine road quality performance indicators; target technical identification refers to the identification used to distinguish the quality performance indicators of road sections. Road sections with the same quality performance indicators are marked with the same target technical identification.

2. The intelligent prediction method for pavement maintenance time according to claim 1 is characterized in that: The method of generating a plurality of factor index time relationship information based on the vehicle monitoring information, road weather information and road quality index corresponding to a plurality of road sections based on the target technical identification, and creating a road degradation model based on the plurality of factor index time relationship information includes: Based on the target technical identifier, vehicle monitoring information, road weather information and pavement quality index of the same road section are obtained and input into the data law analysis model, and the influence of each factor item in the vehicle monitoring information and road weather information on the pavement quality index accumulated over time is analyzed to generate a plurality of factor index time relationship information; Create a pavement degradation model based on the initial pavement quality index and the time relationship information of several factor indices; The technical identifier refers to an identifier used to distinguish technical indicators of road sections; the factor item refers to a factor item that may cause damage to the road surface quality; and the road surface degradation model refers to an algorithm model used to evaluate the reduction of the road surface quality index due to the influence of various factor items.

3. The intelligent prediction method for pavement maintenance time according to claim 1 is characterized in that: The vehicle monitoring information also includes vehicle lane information and vehicle speed information associated with the passing vehicle identification; and also includes: Evaluate the lane average speed and lane change rate of each lane based on the vehicle monitoring information of the target road section; Based on the target technical identifier, the lane average speed, lane change rate, road weather information and pavement quality index of each lane of the same road section are obtained and input into the data law analysis model, and the influence of different pavement quality indexes on the lane average speed and lane change rate of each lane under several weather conditions is analyzed to generate several average speed index relationship information and lane change rate index relationship information; Determine an average speed threshold and a lane change rate threshold for each lane according to a number of average speed index relationship information, lane change rate index relationship information and a preset minimum road quality index; The lane average speed and lane change rate of each lane are compared with the corresponding average speed threshold and lane change rate threshold. When the average speed of any lane is lower than the corresponding average speed threshold or the lane change rate of any lane is higher than the corresponding lane change rate threshold, a lane maintenance alarm message is generated; the lane change rate refers to the quotient of the number of changes in the passing vehicle identification of vehicles exiting the lane that is different from the passing vehicle identification of vehicles entering the lane and the number of vehicles entering the lane. When the number of vehicles exiting the lane is less than the number of vehicles entering the lane, a preset distinguishing mark of the number of shortages is added to the passing vehicle identification information of the vehicles exiting the lane, wherein the preset distinguishing mark should be different from any possible passing vehicle identification.

4. The intelligent prediction method for pavement maintenance time according to claim 3 is characterized by: The lane maintenance alarm information includes a road section mark and a lane mark; When the average speed of any lane is lower than the corresponding average speed threshold or the lane change rate of any lane is higher than the corresponding lane change rate threshold, after the lane maintenance alarm information is generated, the method further includes: Determine the target road section to be maintained and the target lane to be maintained based on the lane maintenance alarm information, determine the traffic flow data of the target road section to be maintained based on the vehicle monitoring information, determine the number of lanes on both sides of the target lane to be maintained, define the lane on the side with fewer lanes as a narrow side lane, and define the lane on the side with more lanes as a wide side lane; The traffic flow data and the preset congestion classification rules are used to determine the congestion level of the target road section to be maintained, wherein the congestion level includes low level, medium level and high level; When the congestion level of the target section to be maintained is high, the target lane to be maintained is determined as the maintenance lane; when the congestion level of the target section to be maintained is medium, the target lane to be maintained and the narrow side lane are defined as the maintenance lane; when the congestion level of the target section to be maintained is low, the target lane to be maintained and the wide side lane are defined as the maintenance lane; based on the proportion of the maintenance lanes to be maintained relative to the total number of lanes in the target section to be maintained, the corresponding quality index recovery value is calculated to reset the initial pavement quality index of the pavement degradation model; The maintenance lane refers to a lane that needs to perform maintenance work; when the number of lanes on both sides of the target lane to be maintained is equal, the slow lane is defined as a narrow side lane; when the number of narrow side lanes is 0, a lane in the wide side lane away from the target lane to be maintained is defined as an exclusion maintenance lane, and the exclusion maintenance lane cannot be defined as a maintenance lane.

5. Intelligent prediction system for pavement maintenance time, characterized by: The intelligent prediction method for pavement maintenance time applied to any one of claims 1 to 4 comprises: A target technical identification acquisition module is used to acquire the construction technical documents of the target road section to determine the corresponding target technical identification and initial maintenance cycle information; The vehicle weather information acquisition module is used to obtain the vehicle monitoring information of the target road section monitoring station and the upstream and downstream monitoring stations, and obtain the road weather information corresponding to the target road section; A pavement degradation model creation module is used to obtain pavement inspection data to calculate a pavement quality index, generate time relationship information of several factor indices based on vehicle monitoring information, road weather information and pavement quality index corresponding to several road sections of the target technical identification, and create a pavement degradation model based on the time relationship information of several factor indices; A modified maintenance time calculation module is used to obtain vehicle monitoring prediction information and road weather prediction information of the target road section and input them into the road degradation model to generate index time prediction data, and calculate the modified maintenance time information based on the index time prediction data and a plurality of preset road maintenance thresholds; The initial maintenance cycle information includes several levels of standard cycles of the target road section; the vehicle monitoring information includes several passing vehicle identifications and vehicle load data; the road meteorological information includes several meteorological factor data related to road surface deterioration; wherein, in the acquisition of road inspection data to calculate the road surface quality index, the calculation formula of the road surface quality index is: PQI t =X 1t P1+X 2t P2+X 3t P3+X 4t P4 Among them, the PQI t is the road quality index at time t. The road inspection data at time t includes the flatness parameter X 1t , damage parameter X 2t , bearing capacity parameter X 3t , Anti-slip ability parameter X 4t , P1, P2, P3, and P4 are weight coefficients corresponding to each road inspection data; Construction technical documents include construction drawings and technical indicators, and refer to technical documents used to determine road quality performance indicators; target technical identification refers to the identification used to distinguish the quality performance indicators of road sections. Road sections with the same quality performance indicators are marked with the same target technical identification.

6. The intelligent prediction system for pavement maintenance time according to claim 5 is characterized in that: Also includes: A lane state evaluation module is used to evaluate the lane average speed and lane change rate of each lane based on the vehicle monitoring information of the target road section; The lane state index relationship analysis module is used to obtain the lane average speed, lane change rate, road weather information and pavement quality index of each lane of the same road section based on the target technical identification and input them into the data law analysis model to analyze the influence of different pavement quality indexes on the lane average speed and lane change rate of each lane under several weather conditions, so as to generate several average speed index relationship information and lane change rate index relationship information; A lane-related threshold determination module, used to determine an average speed threshold and a lane change rate threshold of each lane according to a number of average speed index relationship information, lane change rate index relationship information and a preset minimum road quality index; A lane maintenance alarm information generating module is used to compare the lane average speed and lane change rate of each lane with the corresponding average speed threshold and lane change rate threshold, and generate lane maintenance alarm information when the average speed of any lane is lower than the corresponding average speed threshold or the lane change rate of any lane is higher than the corresponding lane change rate threshold; The vehicle monitoring information also includes vehicle lane information and vehicle speed information associated with the passing vehicle identification; the lane change rate refers to the quotient of the number of changes in the passing vehicle identification of vehicles leaving the road section that is different from the passing vehicle identification of vehicles entering the road section and the number of vehicles entering the road section.

7. The intelligent prediction system for pavement maintenance time according to claim 5 is characterized in that: Also includes: A target lane to be maintained analysis module is used to determine a target road section to be maintained and a target lane to be maintained based on lane maintenance alarm information, determine traffic flow data of the target road section to be maintained based on the vehicle monitoring information, determine the number of lanes on both sides of the target lane to be maintained, define the lane on the side with fewer lanes as a narrow side lane, and define the lane on the side with more lanes as a wide side lane; A congestion level determination module is used to determine the congestion level of the target road section to be maintained by combining the traffic flow data and the preset congestion classification rules, wherein the congestion levels include low level, medium level and high level; A maintenance lane determination module is used to determine the target lane to be maintained as the maintenance lane when the congestion level of the target road section to be maintained is high, define the target lane to be maintained and the narrow side lane as the maintenance lane when the congestion level of the target road section to be maintained is medium, and define the target lane to be maintained and the wide side lane as the maintenance lane when the congestion level of the target road section to be maintained is low; A pavement quality initial index resetting module is used to calculate a corresponding quality index recovery value based on the ratio of the maintenance lanes to the total number of lanes in the target road section to be maintained, so as to reset the pavement quality initial index of the pavement degradation model; The lane maintenance alarm information includes a road section mark and a lane mark; the maintenance lane refers to a lane that needs to be maintained; When the number of lanes on both sides of the target lane to be maintained is equal, the slow lane is defined as the narrow side lane; when the number of narrow side lanes is 0, a lane in the wide side lane that is far away from the target lane to be maintained is defined as an exclusion maintenance lane, and the exclusion maintenance lane cannot be defined as a maintenance execution lane.

8. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the intelligent prediction method for pavement maintenance time as described in any one of claims 1 to 4 are implemented.

9. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the intelligent prediction method for pavement maintenance time as described in any one of claims 1 to 4 are implemented.

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